Dynamic Oligopoly and Monetary Policy: A Deep Reinforcement Learning Approach

Job Market Paper

We evaluate the effect of dynamic oligopolistic strategies on the transmission of monetary policy and conclude that concentration increases the effectiveness of monetary policy mainly because fewer firms collude more often, and collusive prices react less to monetary policy. The main innovation of the paper is that we solve the strategic problem of firms by using state-of-the-art artificial intelligence algorithms called Deep Reinforcement Learning. These algorithms learn by experimenting and improving their strategies over time, using only information about their period rewards and the evolution of the state. Additionally, they approximate the policy and value functions using neural nets. This methodology allows us to study market structures with any number of firms, and we generalize the set of strategies to repeated game strategies and non-markovian strategies. We construct a monetary economy with menu costs and oligopolistic competition at the sector level using this approach. After benchmarking with known results in the literature in a game with a finite (but large) horizon, we allow for repeated game strategies by solving the infinite horizon version. We get a range of converging equilibria, from the Markov equilibrium calculated in recent studies to high-markup equilibria that we interpret as tacit collusive equilibria. We find that monetary policy effectiveness, measured by its contribution to the volatility of log consumption, is up to 40% larger with collusive strategies versus non-collusive strategies. By inspecting the converging policies, we observe that collusion is supported by strong reactions to the price of the competition that ensure that deviations are costly. This stronger price complementary accounts for the increased effectiveness. Then, we vary the number of firms per sector and show that fewer firms imply more effective monetary policy, mainly because collusion is easier.

Nonlinearities and Amplification in Dynamic Production Networks

With Vasco Carvalho and Galo Nuño

(draft coming soon, algorithm implementation available here)

We analyze globally a real business cycle model with production networks using deep-learning techniques. First, we find that the nonlinear perfect foresight solution displays significant nonlinearities and endogenous persistence in response to shocks to upstream sectors. Then we compute the full nonlinear solution and find that the main channel by which nonlinearities affect business cycles is by reducing average aggregate consumption and redistributing resources across sectors to avoid the propagation of shocks originating in upstream sectors. The welfare cost of business cycles is one order of magnitude larger than in standard linear models.

The Indirect Effects of Minimum Wage Increases: Evidence from the Hungarian Firm Network

With Javier Quintana, Palma Mosberger and Lajos Szabo

(draft coming soon)

We study the propagation of minimum wage shocks through the firm network, focusing on the 2017 hike in Hungary's minimum wages. The unique aspects of this case include the presence of two distinct minimum wages for skilled and unskilled workers, each increasing at different rates, and the fact that about half of Hungary's regular workforce was earning the minimum wage at this time. By integrating detailed employer-employee social security data with firm-to-firm value-added tax information, we are able to evaluate both the direct and indirect impact on firms. The indirect effects are further categorized into upstream (exposure through suppliers) and downstream (exposure through buyers) effects. We obtain four main results: i) both minimum wage increases had a negative direct impact on employment by affected firms, such that, ceteris paribus, a firm that had average exposure to both minimum wages would have decreased headcount and hours by roughly 6%; ii) there is a positive indirect effect through upstream exposure, and the skill composition of this effect suggest that firms pick up part of the employees who were fired by upstream firms, and; iii) we find strong substitution effects between skilled and unskilled workers, that is, firms that had more exposure to the skilled minimum wage increased their number of unskilled workers, and vice-versa, and; iv) investment increases, especially for firms exposed to the unskilled minimum wage.